Spatio-temporal distribution and influencing factors of norovirus outbreaks in Beijing, China from 2016 to 2020

被引:0
|
作者
Chen, Yanwei [1 ]
Liu, Baiwei [1 ]
Wang, Yu [1 ]
Zhang, Yewu [2 ]
Yan, Hanqiu [1 ]
Li, Weihong [1 ]
Shen, Lingyu [1 ]
Tian, Yi [1 ]
Jia, Lei [1 ]
Zhang, Daitao [1 ]
Yang, Peng [1 ]
Gao, Zhiyong [1 ]
Wang, Quanyi [1 ]
机构
[1] Beijing Ctr Dis Prevent & Control, 16 Hepingli Middle St, Beijing 100013, Peoples R China
[2] Chinese Ctr Dis Control & Prevent, Beijing 102206, Peoples R China
关键词
Norovirus; Acute gastroenteritis; Outbreaks; Epidemiology; Geographical characteristic; SURVEILLANCE; SYSTEM;
D O I
10.1186/s12879-023-08243-7
中图分类号
R51 [传染病];
学科分类号
100401 ;
摘要
BackgroundNoroviruses are a leading cause of acute gastroenteritis (AGE) worldwide. The geographical characteristics of norovirus outbreaks in Beijing and their influencing factors remain unknown. This study aimed to explore the spatial distributions, geographical characteristics, and influencing factors of norovirus outbreaks in Beijing, China.MethodsEpidemiological data and specimens were collected through the AGE outbreak surveillance system in all 16 districts of Beijing. Data on spatial distribution, geographical characteristics, and influencing factors of norovirus outbreaks were analyzed using descriptive statistics methods. We measured spatial, geographical clustering of high- or low-value deviance from random distribution using Z-scores and P-values as statistical significance measures with Global Moran's I statistics and Getis-Ord Gi in ArcGIS. Linear regression and correlation methods were used to explore influencing factors.ResultsBetween September 2016 and August 2020, 1,193 norovirus outbreaks were laboratory-confirmed. The number of outbreaks varied seasonally, typically peaking in spring (March to May) or winter (October to December). Outbreaks primarily occurred around central districts at the town level, and spatial autocorrelation was evident in both the entire study period and in individual years. Hotspots of norovirus outbreaks in Beijing were primarily found in contiguous areas between three central districts (Chaoyang, Haidian, Fengtai) and four suburban districts (Changping, Daxing, Fangshan, Tongzhou). The average population numbers, mean number of all schools, and mean number of kindergartens and primary schools for towns in central districts and hotspot areas were higher than those in suburban districts and non-hotspot areas respectively. Additionally, population numbers and densities of kindergartens and primary schools were influencing factors at the town level.ConclusionsHotspots of norovirus outbreaks in Beijing were in contiguous areas between central and suburban districts with high populations, and high kindergarten and primary school densities were the likely driving forces. Outbreak surveillance needs to focus on contiguous areas between central and suburban districts with increased monitoring, medical resources, and health education.
引用
收藏
页数:12
相关论文
共 50 条
  • [31] Analysis on the spatio-temporal evolution and influencing factors of China's grain production
    Li, Shaoting
    Zhang, Daojun
    Xie, Yuan
    Yang, Chao
    [J]. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2022, 29 (16) : 23834 - 23846
  • [32] Spatio-temporal divergence and influencing factors of agritourism integration development in Xinjiang, China
    Peng, Yaping
    Liu, Weizhong
    Xiong, Changjiang
    [J]. SCIENTIFIC REPORTS, 2023, 13 (01)
  • [33] Investigating spatio-temporal characteristics and influencing factors for green energy consumption in China
    Ma, Xiaowei
    Weng, Shimei
    Zhao, Jun
    Liu, Huiling
    Huang, Hongyun
    [J]. GEOSCIENCE FRONTIERS, 2024, 15 (03)
  • [34] Spatio-temporal evolution and influencing factors of China’s ICT service industry
    Weixuan Chen
    Shiwei Zhang
    Dezhou Kong
    Tong Zou
    Yuxi Zhang
    Ali Cheshmehzangi
    [J]. Scientific Reports, 13
  • [35] Spatio-temporal evolution and its influencing factors of China's agricultural competitiveness
    Wei S.
    Li J.
    Li Z.
    Zong G.
    [J]. Dili Xuebao/Acta Geographica Sinica, 2020, 75 (06): : 1287 - 1300
  • [36] Spatio-temporal evolution and influencing factors of urban green development efficiency in China
    Liang Zhou
    Chenghu Zhou
    Lei Che
    Bao Wang
    [J]. Journal of Geographical Sciences, 2020, 30 : 724 - 742
  • [37] Spatio-temporal evolution and influencing factors of China's ICT service industry
    Chen, Weixuan
    Zhang, Shiwei
    Kong, Dezhou
    Zou, Tong
    Zhang, Yuxi
    Cheshmehzangi, Ali
    [J]. SCIENTIFIC REPORTS, 2023, 13 (01)
  • [38] Evolution of Spatio-Temporal Patterns and Influencing Factors of Crop Disasters in the Mainland of China
    Fan, Yanxiang
    Huang, Qingzi
    Shao, Wenzhong
    [J]. Beijing Daxue Xuebao (Ziran Kexue Ban)/Acta Scientiarum Naturalium Universitatis Pekinensis, 2024, 60 (05): : 905 - 916
  • [39] Spatio-temporal evolution and influencing factors of urban green development efficiency in China
    Zhou Liang
    Zhou Chenghu
    Che Lei
    Wang Bao
    [J]. JOURNAL OF GEOGRAPHICAL SCIENCES, 2020, 30 (05) : 724 - 742
  • [40] Analysis on the spatio-temporal evolution and influencing factors of China’s grain production
    Shaoting Li
    Daojun Zhang
    Yuan Xie
    Chao Yang
    [J]. Environmental Science and Pollution Research, 2022, 29 : 23834 - 23846